A major project of this section is the development of new statistical genetics methodology as prompted by the needs of our applied studies and the testing and comparison of novel and existing statistical methods. [unreadable] [unreadable] This year, we have continued our collaboration with Dr. Fabio Marroni, publishing a paper on population isolates of South Tyrol and their value in genetic analyses of complex traits.[unreadable] [unreadable] The project to develop propensity scores in linkage analyses as a method for inclusion of covariate effects has been continued in conjunction with Dr. Betty Doan. This method appears promising in that it is generally more powerful than including the covariates directly into the model, and does not have strongly inflated Type I error rates. We are currently examining factors that affect the performance of this method and are applying it to Dr. Bailey-Wilsons lung cancer data.[unreadable] [unreadable] In addition, we have pursued another project designed to examine the effects of important environmental covariates on power and Type I error in linkage studies. We are simulating traits for which moderate to strong environmentsl risk factors play a role in risk of a disease trait (affected vs. unaffected) and then comparing the performance of various analytic methods that ignore covariates to the performance of methods that incorporate these covariates into the analysis. A manuscript is in preparation describing these results and results have been presented at several scientific meetings.[unreadable] [unreadable] We are currently working on establishing a p-value threshold for genome wide association studies using the number of independent SNPs and blocks within the HapMap database, as well as the Affymetrix and Illumina GWAS panels. Since increased density reduces the number of independent tests, using corrections like Bonferroni are not accurate. Instead, we are proposing to identify the true number of independent SNPs across the genome. [unreadable] [unreadable] We are also developing a perl program to count and visualize the number of extended tracts of homozygosity in dense SNP data. Excess homozgyosity could reflect inbreeding or possible regions of deletions, visualizing these regions by case status will allow us to determine if these regions harbor potential deletion sites.[unreadable] [unreadable] We developed a new approach to error detection and correction in microarray gene expression studies of families. A paper is in press describing this method and its effect on the power of linkage studies that use the resulting phenotypic data. [unreadable] [unreadable] We also examined the effects of intermarker linkage disequilibrium on linkage Type I error and power in varying types of family structures. We found that even small amounts of LD can inflate Type I error, that multigenerational pedigrees are less affected than are nuclear families and that missing parental genotypes exacerbates this effect. A paper presenting these results is in press.[unreadable] [unreadable] Dr. Bailey-Wilson also coauthored a paper giving guidelines for replication of genome wide association studies.[unreadable] [unreadable] Many of these projects are ongoing.